3,21c3
Main reference:
* Ramakrishnan & Gehrke, Data Base Management Systems, 3rd Edition, ISBN 0-07-115110-9.
** Suggested reading: Chapters 1, 2, 3, 4.1, 4.2, 5, 8, 9, 10, 12, 16, 19, 20, 21.
(comment from KW: Judging by the table of content available at Amazon this book repeats much of the subject matter students ought to have already when visiting our course. "Beyond RDBMS" the book seems to be relatively short, only OO- and ORDBMS are covered; XML-DBS seem to be not mentioned at all - XML just as a technique to store text - in RDBMS! Then: Only one chapter for DWH. And when it comes to Data Mining the book is very poor (1 page about Clustering???). I guess it no easy job to find a book covering our subject(s) well-balanced)
* Data Mining: Concepts and Techniques (2000) de Jiawei Han, Micheline Kamber
(comment by KW: There's a new edition - see below under "additional literature")
* Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations (1999) de Ian H. Witten, Eibe Frank
(comment by KW: I only read the German version. From this I have to say that I'm not convinced. I found the book ill structured and imprecise, thus difficult to understand. Advantage, on the other hand: the authors keep running an open Data Mining software project - "WEKA")
* Data Mining (Techniques appliquées au marketing, à la vente et aux services clients) (1997) de Berry
* Principles of Data Mining (2001) de David J. Hand, Heikki Mannila, Padhraic Smyth
(comment by KW: very theoretical, in my opinion)
*Data Mining and Statistical Analysis Using SQL (2001) de Robert P. Trueblood, John N. Lovett, Jr
* Applied Data Mining (Statistical Methods for Business and Industry) (2003) de Paolo Giudici
* Data Mining (Introductory and Advanced Topics) (2003) de Margaret H. Dunham
* Data Mining (A Tutorial-Based Primer) (2003) de Richard J. Roiger, Michael W. Geatz
* Baeza-Yates / Ribeiro-Neto: Modern Information Retrieval, New York, 1999, ISBN 0-201-39829-X
!!! Main references/Suggested reading
23,30c5,56
Additional literature:
* Han / Kamber: Data Mining. Concepts and Techniques, 2nd ed., San Francisco 2006, ISBN 978-1-55860-901-3
* Berry / Linoff: Data Mining Techniques, 2nd ed., Indianapolis 2004, ISBN 0-471-47064-3
(comment by KW: Practically oriented, with less focus on algorithms)
* tbd.
* Database Management:
** "Data Base Management Systems", Ramakrishnan & Gehrke, 3rd Edition, ISBN 0-07-115110-9.
** Chapters 1, 2, 3, 4.1, 4.2, 5, 8, 9, 10, 12, 16, 19, 20, 21.
** (comment from KW: Judging by the table of content available at Amazon this book repeats much of the subject matter students ought to have already when visiting our course. "Beyond RDBMS" the book seems to be relatively short, only OO- and ORDBMS are covered; XML-DBS seem to be not mentioned at all - XML just as a technique to store text - in RDBMS! Then: Only one chapter for DWH. And when it comes to Data Mining the book is very poor (1 page about Clustering???). I guess it no easy job to find a book covering our subject(s) well-balanced)
*** (comment from TO: for the old and some new stuff Kemper/Eickler: Datenbanksysteme, Oldenbourg 2006 may be relevant)
* Data Warehousing, Decision Support and Information Retrieval => no books
** tbd.
!!!Further Teaching Material
!!!! Part 1: Database Management
* "Datenbanksysteme", Kemper & Eickler, Oldenbourg 2006.
* "SQL 1999 and SQL 2003", Türker, Dpunkt Verlag, 2003. (may be relevant; in german)
** (comment from SK: This is ok but rather a manual than a reading book).
* "Objektrelationale Datenbanken", Türker & Saake, Dpunkt Verlag, 2005. (in german)
* A small german book: db4o by P. Römer, L. Visengeriyeva, entwickler.press, 2007
* Objektorientierte und objekt-relationale Datenbanken, Meier/Wüst, dpunkt, 2003
* Xquery, P. Walmsley, O’Reilly, 2007
* XML Schema, Eric van der Vlist, O’Reilly, 2002
* Enterprise JavaBeans 3.0, Burke/ Monson-Haefel, O’Reilly, 2006
* EJB3 in action, Panda/ Rahman/ Lane, Manning, 2007 (also availabe as ebook)
* More french books here?
!!!! Part 2: Data Warehouse and OLAP Technology
* "The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling (Second Edition)", Kimball, Ross, Wiley, 2002. ISBN 0471200247 -- The "classical" book
* Data-Warehouse-Systeme; Bauer, Günzel; Dpunkt Verlag, 2004
!!!! Part 3: Data Mining (and Data Analysis):
* "Data Mining: Concepts and Techniques", Jiawei Han & Micheline Kamber, 2nd ed., San Francisco 2006, ISBN 978-1-55860-901-3
* "Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations" (1999) de Ian H. Witten, Eibe Frank
** (comment by KW: I only read the German version. From this I have to say that I'm not convinced. I found the book ill structured and imprecise, thus difficult to understand. Advantage, on the other hand: the authors keep running an open Data Mining software project - "WEKA")
* "Data Mining Techniques", Berry & Linoff, 2nd ed., Indianapolis 2004, ISBN 0-471-47064-3
** (comment by KW: Practically oriented, with less focus on algorithms)
** Data Mining (Techniques appliquées au marketing, à la vente et aux services clients) (1997) de Berry
* "Principles of Data Mining" (2001) de David J. Hand, Heikki Mannila, Padhraic Smyth
** (comment by KW: very theoretical, in my opinion)
* "Data Mining and Statistical Analysis Using SQL" (2001) de Robert P. Trueblood, John N. Lovett, Jr
* "Applied Data Mining (Statistical Methods for Business and Industry)" (2003) de Paolo Giudici
* "Data Mining (Introductory and Advanced Topics)" (2003) de Margaret H. Dunham
* "Data Mining (A Tutorial-Based Primer)" (2003) de Richard J. Roiger, Michael W. Geatz
* "Data Mining" by H. Petersohn; Oldenbourg, 2005 (in German, TO)
!!!!Part 4: Information Retrieval
* "Modern Information Retrieval", Baeza-Yates & Ribeiro-Neto, New York, 1999, ISBN 0-201-39829-X, [http://www2.dcc.ufmg.br/livros/irbook/ Web].
* "Introduction to Information Retrieval", Manning C., P. Raghavan & H. Schütze, Cambridge University Press, 2008, ISBN 0521865719, [http://www-csli.stanford.edu/~hinrich/information-retrieval-book.html Web].
* "Information Retrieval. Suchmodelle und Data-Mining-Verfahren für Textsammlungen und das Web", Ferber, Heidelberg, 2003, ISBN 3-89864-213-5 (KW: concise book in German) [http://information-retrieval.de/irb/irb.html Web-Buch].
Back to ModuleGroupDataManagement
Main reference:
- Ramakrishnan & Gehrke, Data Base Management Systems, 3rd Edition, ISBN 0-07-115110-9 .
- Suggested reading: Chapters 1, 2, 3, 4.1, 4.2, 5, 8, 9, 10, 12, 16, 19, 20, 21.
(comment from KW: Judging by the table of content available at Amazon this book repeats much of the subject matter students ought to have already when visiting our course. "Beyond RDBMS" the book seems to be relatively short, only OO- and ORDBMS are covered; XML-DBS seem to be not mentioned at all - XML just as a technique to store text - in RDBMS! Then: Only one chapter for DWH. And when it comes to Data Mining the book is very poor (1 page about Clustering???). I guess it no easy job to find a book covering our subject(s) well-balanced)
- Data Mining: Concepts and Techniques (2000) de Jiawei Han, Micheline Kamber
(comment by KW: There's a new edition - see below under "additional literature")
- Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations (1999) de Ian H. Witten, Eibe Frank
(comment by KW: I only read the German version. From this I have to say that I'm not convinced. I found the book ill structured and imprecise, thus difficult to understand. Advantage, on the other hand: the authors keep running an open Data Mining software project - "WEKA")
- Data Mining (Techniques appliquées au marketing, à la vente et aux services clients) (1997) de Berry
- Principles of Data Mining (2001) de David J. Hand, Heikki Mannila, Padhraic Smyth
(comment by KW: very theoretical, in my opinion)
- Data Mining and Statistical Analysis Using SQL (2001) de Robert P. Trueblood, John N. Lovett, Jr
- Applied Data Mining (Statistical Methods for Business and Industry) (2003) de Paolo Giudici
- Data Mining (Introductory and Advanced Topics) (2003) de Margaret H. Dunham
- Data Mining (A Tutorial-Based Primer) (2003) de Richard J. Roiger, Michael W. Geatz
- Baeza-Yates / Ribeiro-Neto: Modern Information Retrieval, New York, 1999, ISBN 0-201-39829-X
Additional literature:
- Han / Kamber: Data Mining. Concepts and Techniques, 2nd ed., San Francisco 2006, ISBN 978-1-55860-901-3
- Berry / Linoff: Data Mining Techniques, 2nd ed., Indianapolis 2004, ISBN 0-471-47064-3
(comment by KW: Practically oriented, with less focus on algorithms)
